【摘要】 海洋态势感知与目标观测技术正向着自动化、智能化发展。光电监控系统作为海洋目标活动态势感知中不可或缺的必要手段,在面向长期无人值守的持续海上预警观测应用场景中,其自主运行能力受到极大考验。本文基于多年研究以及相关项目实践,提出了基于机器视觉的海上目标智能化预警观测的一般过程模型与相关的技术实现方法,通过基于深度学习的目标识别模型和一体化的联动跟踪机制驱动光电传感器智能自主运行,在全自动托管的情况下实现目标发现、跟踪、识别、取证、再发现闭环持续工作,为海上目标活动视觉特征提取与信息服务提供有力支撑。更多还原

【Abstract】 Maritime state awareness and marine object observation technology are developing towards automation and intellectualization. For the photoelectric monitoring system,which is the core means of maritime state awareness and target activity forensics,the ability of autonomous operation is greatly tested under the actual situation of long-term unattended observation. Based on many years of research and related project practice,this paper presents the general process and technical method of intelligent early warning and observation of marine targets based on machine vision. The intelligent autonomous operation of photoelectric sensors is driven by the target recognition model based on deep learning and the integrated linkage tracking mechanism,which provides strong support for visual feature extraction and information service of marine target activities.更多还原